Complete 2-in-1 Python for Business and Finance Bootcamp
Data Science, Statistics, Hypothesis Tests, Regression, Simulations for Business & Finance: Python Coding AND Theory A-Z
Created by Alexander Hagmann | 30.5 hours on-demand video course
This is the first ever comprehensive Python Course for Business & Finance Professionals. You will learn and master Python from Zero and the full Python Data Science Stack with real Examples and Projects taken from the Business & Finance world.
This isn´t just a coding course. You will understand and master all required theoretical concepts behind the projects and the code from scratch. You will become an expert not only in Python Coding but also in
- Business & Finance (Time Value of Money, Capital Budgeting, Risk, Return & Correlation, Monte Carlo Simulations, Quality and Risk Management in Production and Finance, Mortgage Loans, Annuities and Retirement Planning, Portfolio Theory, Asset Pricing & Factor Models, Value-at-Risk)
- Statistics (descriptive & inferential statistics, Confidence Intervals, Hypothesis Testing, Normal Distribution & Student´s t-Distribution, p-value, Bootstrapping Method, Monte Carlo Simulations, Normality of Returns)
- Regression (Covariance & Correlation, Linear Regression, Multiple Regression and its pitfalls, Hypothesis Testing of Regression Coefficients, Logistic Regression, ANOVA, Dummy Variables, Links to Machine Learning, Fama-French Factor Models)
This course covers in-depth all relevant and commonly used Python Data Science Packages:
- Python from the very Basics (Standard Library)
- Numpy and Scipy for Numeric, Scientific, Financial, Statistical Coding and Simulations
- Pandas to handle, process, clean, aggregate and manipulate Tabular (Financial) Data. You deserve more than just Excel!
- statsmodels to perform Regression Analysis, Hypothesis Testing and ANOVA
- Matplotlib and Seaborn for scientific Data Visualization
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